drug-retrosynthesis

To predict retrosynthetic pathways, submit a target molecule's canonical SMILES string along with a configurable maximum number of steps. The process polls the IBM RXN API until job completion, returning ranked precursor trees with confidence scores for synthetic accessibility estimation.

Synthetic accessibility estimation scores the feasibility of proposed synthesis routes for novel small molecules. By analyzing target SMILES strings, it generates ranked precursor trees with confidence scores, helping cheminformatics teams prioritize plausible candidate synthesis routes for follow-up research.

Yes, an IBM RXN API key is required as an environment variable to authenticate and submit retrosynthesis jobs. The prediction process relies on IBM RXN's transformer models to generate and rank precursor pathways from the target molecule's SMILES input.

Yes, you can control multi-step exploration depth by configuring the maximum number of retrosynthetic steps. This limits the search depth when generating ranked precursor trees, allowing you to balance between computational time and pathway complexity for your target molecule.

The best way to evaluate synthesis routes for undocumented fluorinated analogs is to input the target molecule's SMILES string into a retrosynthesis prediction tool. This generates ranked pathways with confidence scores, helping prioritize candidate synthesis routes for further research exploration.

Retrosynthesis prediction jobs poll the IBM RXN API until a SUCCESS status is achieved. Delays can occur due to complex target SMILES structures or deep multi-step exploration limits. Ensure your API key is valid and the step limit is appropriately configured for the molecule's complexity.